A soft-gated MoE combining EfficientNet-B0, DenseNet-121, and Swin-Tiny reports 92.62% F1-score on an imbalanced potato leaf disease dataset, outperforming single models by 5%.
, author Gopi, R
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
EfficientNetB5 with CBAM reaches 93.3% accuracy on a 1,366-image peach leaf damage dataset and EfficientNetB3 with CBAM reaches 93% macro F1 after transfer to a 180-image local domain.
citing papers explorer
-
Cross-Architectural Mixture-of-Experts with Adaptive Soft Routing for Plant Leaf Disease Classification
A soft-gated MoE combining EfficientNet-B0, DenseNet-121, and Swin-Tiny reports 92.62% F1-score on an imbalanced potato leaf disease dataset, outperforming single models by 5%.